files provided. All subplots share a common colorbar (in red/green/blue). Command line arguments: * `files`: NPY stacks to be plotted. (multiple arguments possible) """ import numpy as np from sys import argv from matplotlib import pyplot as plt from spectacle import plot, io, analyse from spectacle.general import gaussMd # Get the data folder from the command line files = io.path_from_input(argv) roots = [io.find_root_folder(path) for path in files] # Future command line arguments save_to = io.results_folder / "RGBG.pdf" colorbar_label = 40 * " " + "Read noise (ADU)" # Load Camera object cameras = [io.load_camera(root) for root in roots] print(f"Loaded Camera objects: {cameras}") # Load the data data_all = [np.load(path) for path in files] # Demosaick the data RGBGs_all = [camera.demosaick(data) for data, camera in zip(data_all, cameras)]
also included in the histogram. Command line arguments: * `folders`: folders containing the Pearson r maps. These r maps should be NPY stacks generated using linearity_raw.py and/or linearity_jpeg.py. (multiple arguments possible) """ import numpy as np from sys import argv from matplotlib import pyplot as plt from spectacle import io, linearity as lin, plot # Get the data folder from the command line folders = io.path_from_input(argv) roots = [io.find_root_folder(folder) for folder in folders] r_raw_paths = [ root / "intermediaries/linearity/linearity_raw.npy" for root in roots ] r_jpeg_paths = [ root / "intermediaries/linearity/linearity_jpeg.npy" for root in roots ] save_to = io.results_folder # Load Camera objects cameras = [io.load_camera(root) for root in roots] print(f"Loaded Camera objects: {cameras}") def load_jpeg(path): """
Command line arguments: * `folder`: the folder containing linearity data stacks. These should be NPY stacks taken at different exposure conditions, with the same ISO speed. (multiple arguments possible) """ import numpy as np from sys import argv from spectacle import io, plot, linearity as lin from spectacle.general import RMS from matplotlib import pyplot as plt # Get the data folder from the command line folders = io.path_from_input(argv) roots = [io.find_root_folder(f) for f in folders] # Load Camera objects cameras = [io.load_camera(root) for root in roots] print(f"Loaded Camera objects: {cameras}") save_to = io.results_folder # Lists to hold the data for each device intensities_all = [] intensities_error_all = [] mean_raw_all = [] mean_jpeg_all = [] # Loop over the given folders for folder, camera in zip(folders, cameras):